Privacy by Design and Privacy by Default are requirements under Article 25 of the GDPR. The first means taking data protection into account when designing processes, systems and products. The second means configuring default settings to limit data processing to what is necessary. Here are practical steps for implementing both principles in your organization and reducing the risk of violations.
Why address these principles?
The GDPR does not have to be an obstacle. It is a set of activities and processes that you implement in your organization, like any other operational procedures. When you do this well, data protection becomes part of everyday operations rather than a source of problems.
Privacy by Design and Privacy by Default are starting points in this process. They help you:
- design systems and services with data protection built in from day one,
- process only the data that is actually needed by default,
- make the GDPR part of the process rather than a separate box to check.
The procedure for implementing Privacy by Design and Privacy by Default is intended to put personal data protection mechanisms in place when processes, products or services are being designed (Privacy by Design) and to ensure that only the personal data that is necessary is processed by default (Privacy by Default). This requirement is set out in Article 25 of the GDPR and applies in all EU Member States.
What the Privacy by Design and Privacy by Default procedure is for
- GDPR compliance: both principles are mandatory. Failure to implement them creates a risk of an administrative fine.
- Reducing the risk of violations: you lower the likelihood of incidents at the design stage.
- Building trust: you show clients, employees and contractors that their data is handled responsibly.
- Effective data management: you avoid collecting excessive data and limit processing to what is actually needed.
- Safeguards from the outset: you design systems so that data protection is an integral part of them.
- Privacy as the default: you limit data processing to a minimum when it is not absolutely necessary.
Privacy by Design principles
- Proactive, not reactive: you prevent violations instead of responding to them.
- Privacy as the default setting: users do not have to take additional steps for their data to be protected.
- Integrating data protection into processes: data protection is built into IT systems, products and services.
- Data minimization: you process only the data needed for specific purposes.
- Security and control: you apply appropriate technical and organizational safeguards.
- Transparency: users are informed about how their data is processed.
Privacy by Default principles
Privacy by Default means that the default settings for processes, products or services ensure:
- Data minimization: only necessary personal data is processed.
- Limited access: only people who need access can access the data.
- Limited storage period: data is kept only for the required period.
- Security by default: safeguards such as encryption and anonymization are applied without additional action by the user.
What the Privacy by Design and Privacy by Default procedure includes
- Assigning responsibilities: appoint people responsible for implementing the principles, such as the Data Protection Officer or IT administrators.
- Risk analysis: identify potential risks related to data processing.
- Data minimization: determine which data is necessary and how to limit its scope.
- Designing safeguards: implement technical and organizational measures:
- encryption,
- pseudonymization, meaning replacing identifying data with codes that prevent identification without additional information,
- access controls.
- Setting default data protection options, for example:
- data-sharing options turned off,
- forms that collect less data.
- Testing and monitoring: regularly check whether processes comply with Privacy by Design and Privacy by Default.
- Training employees: educate the team on implementing personal data protection principles.
- Documenting actions: record decisions and solutions, for example in a data protection impact assessment (DPIA), a formal analysis of the effect of planned processing on personal data protection.
What to do with the procedure after drafting it
- Apply it at the design stage: use the principles when creating new processes, systems or products.
- Monitor and assess effectiveness: regularly check whether the solutions work properly and whether data is adequately protected.
- Update it: adapt the procedure to new technologies, processes and legal requirements.
- Document actions: record the steps taken to meet Privacy by Design and Privacy by Default requirements.
- Train employees: provide regular training so they understand how to apply the principles in practice.
- Integrate it with other data protection procedures: these principles form part of a broader personal data protection system, such as a retention policy or a procedure for responding to violations.
How AI can support Privacy by Design and Privacy by Default
Proactive system design
AI can support the design of systems that automatically take personal data protection into account. Algorithms identify potential risks while a system is being developed, which can reduce the risk of a privacy violation before deployment.
Automating data protection settings
AI can automatically apply data protection settings in IT systems by minimizing data collection by default and controlling access. This directly supports Privacy by Default: processing is limited to what is necessary without manual configuration.
Monitoring and risk analysis
AI-based systems continuously monitor data processing, analyze risk and detect irregularities. If a violation occurs, AI generates an automatic alert, shortening response time.
Summary
Privacy by Design and Privacy by Default protect personal data from the outset of a system or process and make privacy the default standard. Implementation involves:
- designing safeguards early,
- limiting data processing to what is actually needed,
- regularly monitoring processes for compliance with legal requirements.
If you run a business and process personal data, check whether your processes meet these requirements. If they do not, start with an audit, prepare the documentation and train your team.
Q&A: Privacy by Design and Privacy by Default in practice
1. What does Privacy by Design mean in practice?
It means building personal data protection into the design of processes, systems and products from the start, rather than adding it later. You plan each data processing activity with data security, risk reduction and user privacy in mind.
2. Which technical measures can be used for Privacy by Default?
Privacy by Default means that systems and processes are configured to minimize data collection. In practice, this includes:
- automatic data encryption,
- access restrictions based on permissions,
- data anonymization,
- setting the minimum scope of information to be collected.
3. Which documents and procedures can help ensure compliance with these principles?
Prepare and implement:
- Privacy Policy,
- Record of Processing Activities,
- Data Security Policy,
- Risk analysis.
Also provide regular employee training and GDPR compliance audits. Without these measures, it is difficult to keep procedures aligned with legal requirements.
4. Who should carry out the activities under this procedure?
- IT department: implements technical safeguards and incorporates data protection into system and application projects.
- Project team: designs processes with personal data protection in mind.
- Data Protection Officer (DPO): oversees and advises on applying Privacy by Default and Privacy by Design.
- Legal and compliance department: ensures compliance with legal requirements.
- Project management: decides to apply data protection principles from the outset and as the default setting.
5. How does artificial intelligence support these principles?
AI can help in three areas:
- automating data protection processes: default settings, encryption and access controls,
- monitoring data processing: ongoing risk analysis and detection of irregularities,
- detecting potential violations: automatic alerts and a faster response.
Implementing these principles requires integrating data protection into project processes, minimizing the data collected and conducting regular GDPR compliance audits. Start by auditing current processes, preparing documentation and training the team.
